Generally, vehicle filtering relies on binary value matching of attributes (e.g., a vehicle either has a value of an attribute or it doesn't). For instance, binary value matching may only return vehicles with a price (as an attribute) below a given value (e.g., $30,000). Therefore, when a user is searching for a vehicle, the user may have many attributes that the user may want the vehicle to match. While searching, the user may determine that some of the attributes are more important to the user than other attributes. For the other attributes, the user may be more flexible as to whether the vehicle includes or fails to include the respective attribute. For instance, a user may prefer that the vehicle must be under $30,000, but the vehicle could be less than 45,000 miles, and the vehicle may or may not be red, etc. However, binary value matching makes searching for vehicles difficult with attributes that may be flexible to the user. For instance, binary value matching may have the effect of excluding vehicles that may be considered acceptable to the user.
The present disclosure is directed to overcoming one or more of these above-referenced challenges. The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art, or suggestions of the prior art, by inclusion in this section.